Key result
A proposed Bayesian procedure for the analysis of seasonal variation performed well when sample size and amplitude are small.
Provides a novel Bayesian statistical method for analyzing seasonal variation in small datasets, which may be useful for epidemiological studies.
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May facilitate seasonal analysis in small epidemiological datasets; leaves open validation before wider use.
We propose what appears to be the first Bayesian procedure for the analysis of seasonal variation when the sample size and the amplitude are small. Such data occur often in the medical sciences, where seasonality analyses and environmental considerations can help clarify disease etiologies. The method is explained in terms of a simple physico-geometric setting. We present the Bayesian version of a frequentist test that performs well. Two examples of real data illustrate the procedure's application.
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Osvaldo Marrero (2018) studied this question. Bayesian procedure for analysis of seasonal variation vs. Frequentist test was evaluated. A proposed Bayesian procedure for the analysis of seasonal variation performed well when sample size and amplitude are small.
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